app.py

from transformers import pipeline
import gradio as gr

pipe = pipeline(
    "audio-classification", model="ceefax/distilhubert-finetuned-gtzan"
)

model_id = "ceefax/distilhubert-finetuned-gtzan"
pipe = pipeline("audio-classification", model=model_id)
title = "Genre Classifier"
description = "Genre classifier trained on GTZAN"
# examples = ['/content/Trumpet_to_ambient_music.wav']
interpretation='default'
enable_queue=True

def classify_audio(filepath):
    preds = pipe(filepath)
    outputs = {}
    for p in preds:
        outputs[p["label"]] = p["score"]
    return outputs

demo = gr.Interface(
    fn=classify_audio, inputs=gr.Audio(type="filepath"), outputs=gr.outputs.Label(), title=title,description=description
    # ,examples=examples
    ,interpretation=interpretation,enable_queue=enable_queue
).launch()